Hunt, LE; (2018) Exploring noncoding variation in human diseases and disorders through targeted sequencing and functional prediction. Doctoral thesis (Ph.D), UCL (University College London).

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Abstract

The identification of non-coding single nucleotide polymorphisms (SNPs) and short insertions or deletions (indels) that are causative or contributory to human diseases and disorders is limited by the functional knowledge of the non-coding genome. This work demonstrates multiple approaches to elucidate functional variation in the non-coding genome by using homogenous populations or pedigrees of individuals with shared diseases and disorders, including Obesity, Schizophrenia, Anosmia and Mitochondrial Depletion Syndrome. A vast bank of non-coding variation has been created and can be utilised for population analysis. Using supporting evidence of developmental contributions to the disorders studied and genome interaction data, high coverage sequencing of targeted regions and subsequent bioinformatics analysis suggests multiple new disease-associated non-coding variants. Combining available variant function predictor tools and publicly available functional data, a selection of variants are prioritised as potentially causative or contributory and their affect on the region’s function in development as an enhancer is assessed in Zebrafish. In addition, deep-sequencing and bioinformatics analysis in mouse models of MPV17 deletion contributes to the understanding of mitochondrial depletion syndrome.

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